Claude Equity Research

🤖 Built entirely with Claude Code - demonstrating AI-native development workflows for professional-grade financial tools.

Professional equity research and trading analysis powered by Claude AI, delivering institutional-grade investment insights with Goldman Sachs-style formatting and comprehensive risk assessment.

What It Does

• Institutional-Grade Analysis: Generates professional equity research reports matching Wall Street standards
• AI-Powered Intelligence: Leverages Claude AI for comprehensive fundamental and technical analysis
• Real-Time Data Integration: Pulls live market data, earnings reports, and analyst coverage
• Risk-Adjusted Recommendations: Provides buy/sell/hold ratings with specific price targets and position sizing
• Advanced Market Intelligence: Includes options flow analysis, insider trading activity, and sector positioning

Key Features

Core Analysis Framework

• Executive Summary: Investment thesis with price target and 12-month timeframe
• Fundamental Analysis: Revenue growth, margins, peer comparisons, and forward estimates
• Catalyst Analysis: Near-term and medium-term market drivers with specific dates
• Valuation Models: Bull/base/bear scenarios with probability weighting
• Risk Assessment: Company-specific and macro risks with position sizing guidance (1-5%)
• Technical Context: Support/resistance levels, momentum indicators, and volume analysis

Enhanced Intelligence Features

• Options Flow Analysis: Unusual activity, put/call ratios, implied volatility trends
• Insider Activity Monitoring: Executive buying/selling patterns with dollar amounts
• Sector Positioning: Rotation trends and relative strength vs market indices
• ESG & Governance: Sustainability scores and regulatory compliance assessment

Professional Standards

• Institutional Terminology: EBITDA, P/E ratios, EV/Sales, conviction levels
• Probability Weighting: Bull/base/bear scenarios with percentage allocations
• Legal Protection: Comprehensive disclaimers for educational use
• Data Sourcing: Real-time web search with analyst firm citations

Installation & Setup

Prerequisites

• Claude Code CLI (version 2.0.11 or higher)
• Claude paid subscription (Pro, Team, or Enterprise)
• Internet connection for real-time data retrieval

Installation via Claude Code Plugin (Recommended)

Quick Install - Interactive Menu:

# Step 1: Add the marketplace
/plugin marketplace add quant-sentiment-ai/claude-equity-research

# Step 2: Open the plugin menu
/plugin

# Step 3: Select "Browse Plugins" → find "claude-equity-research" → "Install now"

Alternative - Direct Install:

/plugin marketplace add quant-sentiment-ai/claude-equity-research
/plugin install trading-ideas@claude-equity-research-marketplace

Verify Installation:

/help  # Confirm /trading-ideas:research command is listed

Start Analyzing:

/trading-ideas:research AAPL
/trading-ideas:research NVDA --detailed

Claude Code namespaces plugin commands as <plugin-name>:<command-name>, so the invocation is /trading-ideas:research (not the bare /trading-ideas). If you prefer the bare form, use the manual install below — it copies the command file into your personal ~/.claude/commands/ and registers it as /trading-ideas.

💡 Tip: Restart Claude Code after installation for best results.

For comprehensive plugin documentation, see PLUGIN.md.

Quick Start

1. Install the /trading-ideas command (system-wide):

mkdir -p ~/.claude/commands
curl -o ~/.claude/commands/trading-ideas.md https://raw.githubusercontent.com/quant-sentiment-ai/claude-equity-research/main/commands/trading-ideas/commands/research.md

2. Basic usage:

/trading-ideas AAPL

3. Enhanced analysis:

/trading-ideas HOOD --detailed

Manual Setup via Git Clone

1. Clone the repository:

git clone https://github.com/quant-sentiment-ai/claude-equity-research.git
cd claude-equity-research

2. Copy command to Claude Code:

cp commands/trading-ideas/commands/research.md ~/.claude/commands/trading-ideas.md

Usage Examples

Examples below use the plugin install invocation (/trading-ideas:research). If you followed the manual install path, drop the :research suffix and use the bare /trading-ideas form.

Basic Equity Analysis

/trading-ideas:research AAPL

Output: Comprehensive institutional research report with BUY/SELL/HOLD recommendation

Technology Sector Analysis

/trading-ideas:research NVDA

Features: AI/semiconductor sector positioning, relative valuation vs peers

Financial Services Analysis

/trading-ideas:research JPM

Includes: Interest rate sensitivity, regulatory environment, book value analysis

Growth Stock Analysis

/trading-ideas:research TSLA

Focus: Growth metrics, competitive positioning, volatility assessment

Sample Output Format

# APPLE INC (AAPL) - ENHANCED EQUITY RESEARCH

## EXECUTIVE SUMMARY
BUY with $250 price target (9% upside) over 12 months. Strong Q4 2024 
results driven by iPhone 16 launch and AI integration provide foundation 
for premium product cycle. Balanced risk-reward with established ecosystem moat.

## FUNDAMENTAL ANALYSIS
Q4 2024: Revenue $94.9B (+6% YoY), EPS $1.64 (+12% YoY). iPhone revenue 
$46.2B (~49% of total), Services +12% to $25B with recurring characteristics.

## VALUATION & PRICE TARGETS
Consensus: $242 (range $200-$280)
Bull case: $280 | Base case: $250 | Bear case: $200
Probability weighting: 25%/55%/20%

## RECOMMENDATION: BUY | Conviction: High | Price Target: $250

Command Reference

Repository Structure

claude-equity-research/
├── README.md                     # This file
├── LICENSE                       # MIT License
├── commands/
│   ├── trading-ideas/            # Plugin directory (installed via marketplace)
│   │   ├── .claude-plugin/
│   │   │   └── plugin.json       # Plugin manifest
│   │   └── commands/
│   │       └── research.md       # Slash command (invoked as /trading-ideas:research)
│   └── README.md                 # Command documentation
├── config/
│   ├── config.example.json       # Template configuration
│   └── prompts/                  # Analysis prompt templates
├── examples/
│   └── sample_reports/           # Example analyses (AAPL, HOOD, etc.)
├── docs/
│   ├── methodology.md            # Detailed analysis framework
│   ├── installation.md           # Setup instructions
│   └── customization.md          # Customization guide
├── utils/
│   ├── data_sources.md           # Data source documentation
│   └── validation.py             # Analysis validation tools
└── tests/
    └── test_command.py           # Command functionality tests

Analysis Methodology

Our research framework combines:

Quantitative Analysis

• Financial Statements: Revenue, margins, cash flow analysis
• Valuation Models: Multiple approaches (DCF, comparable company, precedent transaction)
• Technical Indicators: Support/resistance, momentum, relative strength
• Options Analytics: Implied volatility, unusual activity, sentiment indicators

Qualitative Assessment

• Competitive Positioning: Market share, competitive advantages, moat analysis
• Management Quality: Track record, capital allocation, strategic vision
• Regulatory Environment: Industry-specific risks, compliance issues
• ESG Factors: Environmental, social, governance considerations

Risk Management

• Scenario Analysis: Bull/base/bear cases with probability weighting
• Position Sizing: Risk-adjusted allocation recommendations (1-5% typical)
• Stop-Loss Guidance: Downside protection levels
• Correlation Analysis: Portfolio diversification considerations

Data Sources

• Financial Data: SEC filings, earnings reports, company guidance
• Market Data: Real-time pricing, volume, technical indicators
• Analyst Coverage: Wall Street research, price target updates
• News & Sentiment: Financial media, regulatory announcements
• Options Data: Unusual activity, implied volatility, positioning
• Insider Activity: Form 4 filings, executive transactions

Professional Disclaimers

⚠️ Important Legal Notice

This tool is designed for educational and research purposes only. All analysis and recommendations are:

• Not financial advice - For informational purposes only
• Not personalized - Does not consider individual circumstances
• Historical data based - Past performance doesn't guarantee future results
• Requiring due diligence - Users must conduct independent research
• Risk warning included - All investments carry risk of loss

Risk Warnings

• Stock prices are volatile and unpredictable
• AI analysis may contain errors or biases
• Market conditions change rapidly
• Regulatory and company-specific risks may not be fully capt